GoodLads - AI growth manager for your Google Ads account
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AI growth manager for Google Ads accounts. GoodLads generates hypotheses to improve your ROAS or CPA, ships each one in one click - never without your approval - and tracks it on a kanban board to a verdict.
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Hi Product Hunt,
When I worked on launching and optimising @Google Ads for my product @TimeTuna (#1 of the day in December), I found that launching the first campaign from scratch more complicated than filing a tax return in the Netherlands (good job Dutch people). Then after I launched it, I found it hard to keep experimenting consistently to make sure new paid clients are attracted with a good cost of acquisition.
@yannick_veys is the cofounder of GoodLads, and he has 15+ years experience optimising Google Ads for various companies, and he developed a serious of know-hows, which often are different from the recommendations given by Google (one example, if your campaign is limited by budget Google recommends to increase the budget, while Yannick identified that reducing target cost per acquisition could already improve the performance with the same budget).
It felt like it is very natural to bring AI models + Google Ads API + Know How from Yannick and package it as one product.
This is how @GoodLads was born: AI growth manager for your Google Ads account.
Specially for our ProductHunt launch we introduce a 50% promo code: "MAKEITEASY"
Do you find our product name genius or ridiculous?
Pavel & Yannick
Letssss gooooo GoodLads!!
u scoped it to accounts spending 10k to 250k a month, thats specific. how long does a hypothesis sit on the kanban before it gets a verdict?
@niveditha_patluri1 Hey Nivy, well we follow a statistic testing, so it depends on the number of clicks, and the size of the impact. If the impact is huge (e.g. 25% improvement) - it could be visible within a week, if the impact is modest (e.g. 5%), it might take 4 weeks, and very small impact might not be detectable at all. The recommendation is to make sure the experiment runs for at least 2 weeks. What is your usecase?
This looks really awesome! I just want to call out that there are some amazing Google MCPs out there, and your pricing might be a little bit high, especially for professionals who manage more than one login. The idea of paying $1,000 a month to have more than one login, some might find challenging.
That said, your implementation looks awesome! I'd be really excited to use it for something closer to $100 a month, which is what your comparison set looks like. Congrats on the great launch!
@paulgeller
Hi Paul,
I am glad you find it relevant! What is your specific use case? How many accounts would you like to manage? I assume you run an agency or consultancy for other clients? I would love to chat with you to learn more, feel free to book https://timetuna.com/pavel
@pavelk2 I manage about 10 accounts across two MCC logins
@paulgeller awesome. You would be an interesting case. Feel free to book a call, and we can discuss. I would be interested in running a pilot with you.
genius name lol 😂 approval before every change is the usefull part, most smb owners wont trust full autopilot yet
@petrkovacik thanks Petr! Agreed on the approval part. We believe that kanban with approval stages is the right way for AI agents.
Does it change bids and budgets on its own, or queue them for approval?
@tomveber Hi Tom,
It acts in a kanban way proposing ideas, you approve them, then go implemented, then they are tested.
"Never without your approval" is the right guardrail for something that touches live ad spend, but I'd want to know how the hypotheses themselves get generated before trusting the approval step alone - if the suggestions are just generic "raise budget on the winning ad group" advice that any account manager would already do, the AI layer isn't adding much beyond a nicer kanban board. What's an example of a hypothesis it shipped that a human account manager would have missed?
@galdayan I would not say would have missed - there are genius account managers out there :)
Few examples:
- limited by budget - it recommends to reduce the click, so we get more clicks with the same budget. Not every account manager knows that trick
- targeting business clients rather than consumers - it suggested to target API related keywords, which the person running the ads did not think about, and found that recommendation very relevant.
Those are both good examples, thanks for laying them out. The B2B keyword one especially - that's a blind spot that's easy to miss when you're deep in day to day account management. Does GoodLads surface the reasoning behind a suggestion, or just the recommended action itself? I'd want to see the "why" before approving a change on a live account, even with the one-click approval gate.
@galdayan Hey Gal,
Yes it does. I did a PhD 10 years ago. And I decided to apply the academic approach to explaining each hypothesis. it shows a series of observations either from the account data, or external learnings, and generates a hypothesis based on that, so there is a relatively strong understanding what the hypothesis is based on.